PoseGuard: Privacy-First Farm Security at AI SENSE
Farm entry monitoring without surveillance anxiety. Pose-estimation-only approach detects presence and behaviour without capturing or storing facial imagery.
Field Notes & Insights
Research updates, product thinking, and field stories from the intersection of AI and the natural world.
Farm entry monitoring without surveillance anxiety. Pose-estimation-only approach detects presence and behaviour without capturing or storing facial imagery.
Promising AgTech ventures stall not because their technology didn't work, but because of distribution, trust, and the stubborn realities of agricultural sales cycles.
How low-power edge devices transform farm operations by processing soil moisture, temperature, and conductivity data locally — enabling real-time decisions without cloud dependency.
How we built a crop monitoring system that never transmits identifiable imagery off-device — using on-chip inference and differential privacy techniques to protect grower data.
Running federated learning across 12 edge nodes deployed on farms in rural Maryland taught us that real-world FL is messier — and more rewarding — than benchmarks suggest.
How we created a reproducible, community-driven annotation pipeline for camera-trap wildlife imagery — including inter-annotator agreement protocols and quality gates.
Benchmarking seven lightweight computer vision models — from MobileNetV3 to EfficientDet-Lite — against annotated crop health imagery captured in real Maryland farmland conditions.
